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In this paper, we show that it is possible to obtain an optimal configuration variant of Modular Strongrooms (MSR) that satisfies the individual requirements of customers and is most economically advantageous for manufacturers. A model of the automatic configuration system for configuring MSR type MODULPRIM was developed, integrating the procedures for generating product variants, choosing the optimal configuration, and designing detailed products and technological processes. The developed model’s importance lies in its ability to automatically select the optimal configuration from a set of possible configurations on a multidisciplinary basis. The problem of choosing was solved by integrating the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods from the group of Multi-Attribute Decision Making (MADM). Validation of the proposed model was performed on eight examples of Modular Strongrooms type MODULPRIM 5 and showed great opportunities to improve efficiency and effectiveness in the process of innovative product development, as well as to obtain a product configuration with significantly improved quality. The proposed model has a high degree of flexibility and universality; thus, it can be further upgraded and integrated into a company’s business system.

Modern Automatic Speech Recognition (ASR) systems are primarily designed to recognize normal speech. Due to a considerable acoustic mismatch between normal speech and whisper, ASR systems suffer from a significant loss of performance in whisper recognition. Creating large databases of whispered speech is expensive and time-consuming, so research studies explore the synthetic generation using pre-existing normal or whispered speech databases. The impact of standard audio data augmentation techniques on the accuracy of isolated-word recognizers based on Hidden Markov Models (HMM) and Convolutional Neural Networks (CNN) is examined in this research study. Furthermore, the study explores the potential of inverse filtering as an augmentation strategy for producing pseudo-whisper speech. The Whi-Spe speech database, containing recordings in normal and whisper phonation, is utilized for data augmentation, while the internally recorded speech database, developed specifically for this study, is employed for testing purposes. Experimental results demonstrate statistically significant improvement in performance when employing data augmentation strategies and inverse filtering.

To encourage proper waste management for electrical and electronic devices (e-waste), it is necessary to invest heavily in the development of recycling technologies. One way to improve the process is to automate separating the shredded parts of e-waste using a robot. This paper’s literature review, utilizing the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework, showcases potential robotic technologies for e-waste separation. However, the intricate design of these devices can pose significant challenges in their implementation. Various legal, organizational, and sociological obstacles have left Serbia’s e-waste management practice underdeveloped, resulting in an unsatisfactory recycling rate. In this paper, we examined the possibility of using robots in the precise example of recycling refrigerators in a recycling center in Eastern Serbia, concluding that such a solution would have multiple positive effects, both on the employees and the working environment, on the operations of the recycling center itself, and on increasing the e-waste recycling rate in the country.

This study considers the influence of purity and surface area on the thermal and oxidation properties of hexagonal boron nitride (h-BN) nanoplatelets, which represent crucial factors in high-temperature oxidizing environments. Three h-BN nanoplatelet-based materials, synthesized with different purity levels and surface areas (~3, ~56, and ~140 m2/g), were compared, including a commercial BN reference. All materials were systematically analyzed by various characterization techniques, including gas pycnometry, scanning electron microscopy, X-ray diffraction, Fourier-transform infrared radiation, X-ray photoelectron spectroscopy, gas sorption analysis, and thermal gravimetric analysis coupled with differential scanning calorimetry. Results indicated that the thermal stability and oxidation resistance of the synthesized materials were improved by up to ~13.5% (or by 120 °C) with an increase in purity. Furthermore, the reference material with its high purity and low surface area (~4 m2/g) showed superior performance, which was attributed to the minimized reactive sites for oxygen diffusion due to lower surface area availability and fewer possible defects, highlighting the critical roles of both sample purity and accessible surface area in h-BN thermo-oxidative stability. These findings highlight the importance of focusing on purity and surface area control in developing BN-based nanomaterials, offering a path to enhance their performance in extreme thermal and oxidative conditions.

Microplastics (MPs), chlorinated phenols (CPs), polycyclic aromatic hydrocarbons (PAHs) and halogenated benzenes (HBs) are pollutants that are widely present in freshwater systems. As alternatives to conventional plastics, bioplastics are receiving a lot of attention, but there are limited data on their impact on pollutant behavior. This work therefore investigated the impact of pH on the sorption of CPs, PAHs and HBs, as some of the toxic and highly persistent pollutants, on seven different plastics using kinetic and isotherm studies. The pH of the water matrix impacted the adsorption behavior of CPs on all selected MPs, with the highest degree of adsorption occurring at pH 7 for the majority of the selected CPs. The highest adsorption affinity of CPs on the MPs, at pH 7, was obtained for 4-chlorophenol and 2,4-dichlorophenol on powdered polyethylene standard (qt = 221 μg/g), while the lowest was obtained for the adsorption of pentachlorophenol on polyethylene terephthalate (qt = 25 μg/g). On the other hand, the pH value of the water matrix did not affect the adsorption of halogenated benzenes and PAHs on MPs. The pseudo-second-order rate model fit the adsorption kinetics data of all experiments. The results obtained for the adsorption of CPs on MPs indicated a lower sorption affinity of CPs with MPs at pH 4 and pH 10 compared to pH 7. The Langmuir isotherm, at pH 7, implied that 4-chlorophenol’s adsorption affinity was not significantly influenced by the type of MPs. On the other hand, at pH 7, the adsorption of 2,4-dichlorophenol, 2,4,6-trichlorophenol and pentachlorophenol varied greatly, with powdered MP types showing the highest affinity for CP adsorption. Furthermore, the obtained adsorption isotherm results imply that electrostatic attraction, hydrogen bonds, π-π interactions and van der Waals interactions, are an integral part of adsorption mechanisms of the CPs on the MPs.

Studying the interaction of inorganic systems with organic ones is a highly important avenue for finding new drugs and treatment methods. Tumor cells show an increased demand for amino acids due to their rapid proliferation; thus, targeting their metabolism is becoming a potential oncological therapeutic strategy. One of the inorganic materials that show antitumor properties is titanium dioxide, while its doping was found to enhance interactions with biological systems. Thus, in this study, we investigated the energy landscape of glutamine (L), an amino acid, on pristine and doped TiO2 surfaces. We first locally optimized 2D-slab structures of pristine and Au/Ag/Cu-doped anatase (001 and 101 surfaces) and similarly optimized a single molecule of glutamine in vacuum. Next, we placed the pre-optimized glutamine molecule in various orientations and on a variety of locations onto the relaxed substrate surfaces (in vacuum) and performed ab initio relaxations of the molecule on the substrate slabs. We employed the DFT method with a GGA-PBE functional implemented in the Quantum Espresso code. Comparisons of the optimized conformations and electronic structures of the amino acid in vacuum and on the surfaces yield useful insights into various biological processes.

A description of magnetic hysteresis is important for the prediction of losses in soft magnetic materials. In this paper, a viscosity-type equation is used to describe dynamic hysteresis loops in an amorphous ring core for symmetric excitation, as prescribed by international standards. The value of the exponent appearing in the viscosity-based equation can be assumed to be constant if the maximum induction is away from the saturation value. The viscosity-type equation is used to describe the shape variation of magnetization curves due to eddy currents in different time and space scales. Modeling is carried out for various excitation frequencies and induction amplitudes. The discrepancies between the experimental and modeled curves (and also losses) are acceptable in the wide range of the frequency and maximum induction. The paper indicates that the viscosity-type effects, mostly due to eddy currents generated in the conductive material, play an important role in energy dissipation at increased excitation frequencies. The modeling results might be interesting to the designers of magnetic circuits.

This study analyzes the grid-connected PV system performances over a 10-year period under temperate continental conditions in Niš. Based on the experimental results, we found the following: the 10-year yearly average values of PV system efficiency, Yf, CF, and PR are 10.49%, 1178.51 kWh/kWp, 13.45%, and 0.87, respectively. The yearly average value of PV performances for a 10-year measurement indicates that the behavior of the given PV system over 10 years does not change significantly. Besides, a mathematical prediction model was obtained through regression analysis, and ANOVA was applied for testing the model’s validity. It is shown that the obtained model is statistically significant and enables prediction better than a simple average, the mean values of PV electricity are not changed statistically significantly over the 10 observed years, and there is a statistically significant difference in POA mean radiation during the months over 10 years. Based on the obtained model and POA radiation values, a prediction of the PV system output can be made for similar PV installations. The analysis presented in this study significantly impacts energy prediction, PV energy modeling, and the economics and profitability of the grid-connected PV system utilization, as well as the PV systems’ operation planning and maintenance.

In this study, the adsorption equilibrium and diffusivity parameters of p-nitrophenol were estimated for water containing different concentrations of secondary amides. Commercial powdered activated carbon was used as an adsorbent. The external mass transfer coefficient (kf), the surface diffusion coefficient (Ds) and the standard free Gibbs energy were calculated for p-nitrophenol in the presence of different secondary amide concentrations. The analysis established that there are correlations between structural parameters of amides, on the one hand, and diffusion and thermodynamic parameters for p-nitrophenol adsorption process, on the other. It was noticed that voluminous hydrophobic amides decreased the adsorption capacity of p-nitrophenol on activated carbon. On the basis of the results obtained for external mass transfer coefficients, it is assumed that amides cause the reduction of adsorption capacity of p-nitrophenol onto activated carbon by concentrating at the solid/liquid interface. Keywords: Adsorption, Amides, Natural organic matter, P-nitrophenol

Many scientific papers that deal with the topic of the pedestrian environment use a predefined form for assessing or evaluating its quality as a basic methodological instrument. The aim of this research is to emphasize the dimension of the available audit tools or methodologies in order to develop a full-scale database of indices that can be used for the measurement and evaluation of the pedestrian environment. By analyzing 115 research papers selected according to predefined selection criteria, the basic methodological apparatus or the evaluation instrument was observed. Based on the analysis carried out in this way, a number of 40 valid instruments were identified by which it was possible to evaluate the pedestrian environment. The observed instruments have a high level of reliability according to the high values of the ICC coefficient, IRR test, or Kappa value. There are 193 items for the evaluation of the pedestrian environment that were derived from the observed instruments. The items were arranged over seven groups regarding the quality of the pedestrian environment, namely, Functionality, Safety, Comfort, Mobility, Environment, Connectivity, and Aesthetics. On average, the items distributed over those seven groups are in use throughout the entire pool of instruments at the level of 47.41% across all groups. There are 30 instruments or methodologies that are objectively based, 4 subjectively oriented, and 6 with elements of both approaches. Of the instruments, 14 measure and assess the pedestrian environment through a quantitative data set, while 20 are designed for qualitative assessment. Only six of the instruments contain both qualitative and quantitative measuring items. A large percentage of analyzed papers that use a predefined methodology or instrument indicate the need to deepen the field of research and to include additional aspects that would give more authoritative results.

This paper describes a methodological approach to the creation of a strategic planning ontology (SPO) for local governments. The aim of the given ontology is to provide a semantic description of the development strategy, involved stakeholders, and tools to improve the decision-making process for selecting the most valuable strategic objectives for the economy of the region. The novelty of the research presented in this paper is reflected by the development of an ontological model of actions and reasons, that is, semantically described combinations of activities and requirements that are defined by development strategies. The proposed ontology can provide answers to questions such as: what are the development priorities? How will those priorities be implemented? Who will be responsible for implementation? Why are they being implemented in the first place? We answer the question, “why specific development goals are chosen?”. Answers are given as semantic representations of the economic impact on a region’s industry. The ontology-driven simulation methods that are proposed in this paper provide the possibility of simulating the effects and results of the chosen development strategy goals, evaluate the actions taken, and ensure support for the selection of the best alternative in the process of defining objectives for the development strategy.

Environmental pollution is an emerging global issue. Heterogenous photocatalytic degradation, which belongs to the advanced oxidation processes, is a promising sustainable technique for the removal of harmful pollutants (e.g., pharmaceuticals) from natural resources (surface and underground waters), as well as wastewaters. In our study, we examined the efficiency of photocatalytic degradation (with TiO2 and ZnO as photocatalysts) of tolperisone hydrochloride (TLP) and the effect of TLP and its degradation intermediates on germination, photosynthetic capacity, and biomass production of wheat. According to the UFLC-DAD and LC–ESI–MS results, we found that the complete degradation of TLP can be reached after 60.83 min of UV irradiation using TiO2 as a photocatalyst. Furthermore, we determined that germination, biomass production, and chlorophyll b (Chl b) were not related to the percentage of TLP after irradiation. Chlorophyll a (Chl a) (r = −0.61, p ≤ 0.05), Chl a+b (r = −0.56, p ≤ 0.05), and carotenoid (car) (r = −0.57, p ≤ 0.05) were strongly inversely (negatively) correlated with TLP, while Chl a+b/car (r = 0.36, p ≤ 0.05) was moderately (positively) related.

In the last decade, increased awareness of the importance of preserving old masonry structures of cultural heritage has turned to the development of sustainable strategies for their reconstruction and seismic strengthening. This research includes the analysis and determination of the necessary measures due to the assessment of the condition of the constructive and structural parts of the buildings belonging to the old City Fortress in Novi Pazar. In this study, the fragility and vulnerability of the building is identified in order to sanction and recommend strengthening and seismic resistance to potentially strong levels of earthquakes, preserving the original structure of the building and its authenticity and integrity. The presented techniques aim to improve seismic performance and preserve structures for future generations, with the least impact on changing the value of the investigated cultural heritage. On the other hand, due to the modern demands of society, it is recommended to implement digital conservation and management of cultural heritage in order to create new content and ensure accessibility for all.

The X-ray fluorescence spectrometry and the MA.BM.006 reference spectrophotometric methods were used to determine the content of SiO2 (%) in bauxites from different deposits. The treatment of samples prior to the analysis involved the following steps: annealing, melting using the borax method, and the formation of beads. Certified reference bauxite samples were used for the calibration curve. The calibration curve was produced with the correlation coefficient of r =0.9999 and the standard error of S = 0.0246. The average residual value between the content of SiO2 determined using the XRF method, and the reference method was 0.045, with a standard deviation of 0.068. The XRF method was statistically verified by the F- and t- tests (using the standard sample and the reference method). The values obtained in the tests show that the XRF method yields accurate results and that there are no standard errors.

Machine learning techniques are ever prevalent as datasets continue to grow daily. Associative classification (AC), which combines classification and association rule mining algorithms, plays an important role in understanding big datasets that generate a large number of rules. Clustering, on the other hand, can contribute by reducing the rule space to produce compact models. The above-mentioned facts were the main motivation for this research work. We propose a new distance (similarity) metric based on “direct” and “indirect” measures and explain the overall importance of this method, which can produce compact and accurate models. Specifically, we aim to employ agglomerative hierarchical clustering to develop new associative classification models that contain a lower number of rules. Furthermore, a new strategy (based on the cluster center) is presented to extract the representative rule for each cluster. Twelve real-world datasets were evaluated experimentally for accuracy and compactness, and the results were compared to those of previously established associative classifiers. The results show that our method outperformed the other algorithms in terms of classifier size on most of the datasets, while still being as accurate in classification.

Under exceptional circumstances, light and molecules bond together, creating new hybrid light–matter states with far-reaching consequences for these strongly coupled entities. The present article describes the quantum-mechanical foundation of strong-coupling and experimental evidence for molding the radiation properties of nanoprobes by strong-coupling. When applied to tracing and marking, the new fluorometry technique proposed here, which harnesses strong-coupling, has a triple advantage compared to its classical counterparts such as DNA tracing. It is fast, and its signal-to-noise ratio can be improved by spectral filtering; moreover, it reveals a specific quantum signature of the strong-coupling, which is extremely difficult to reproduce classically, thereby opening the door to new anti-counterfeiting strategies.

Microservice Architecture (MSA) is a rising trend in software architecture design. Applications based on MSA are distributed applications whose components are microservices. MSA has already been adopted with great success by numerous companies, and a significant number of published papers discuss its advantages. However, the results of recent studies show that there are several important challenges in the adoption of microservices such as finding the right decomposition approach, heterogeneous technology stacks, lack of relevant skills, out-of-date documentation, etc. In this paper, we present Silvera, a Domain-Specific Language (DSL), and a compiler for accelerating the development of microservices. Silvera is a declarative language that allows users to model the architecture of microservice-based systems. It is designed so that it can be used both by inexperienced and experienced developers. The following characteristics distinguish Silvera from similar tools: (i) lightweight and editor-agnostic language, (ii) built with heterogeneity in mind, (iii) uses microservice-tailored metrics to evaluate the architecture of the designed system, and (iv) automatically generates the documentation. Silvera’s retargetable compiler transforms models into runnable code and produces the documentation for each microservice in the model. The compiler can produce code for any programming language or framework since code generators are registered as plugins. We present a case study that illustrates the use of Silvera and also discuss some current limitations and development directions. To evaluate Silvera, we conducted a survey based on A Framework for Qualitative Assessment of DSLs (FQAD), where we focused on the following DSL characteristics: functional suitability, usability, reliability, productivity, extendability, and expressiveness. Overall, the survey results show that Silvera satisfies these characteristics.

Currently, the computational power present in the sensors forming a wireless sensor network (WSN) allows for implementing most of the data processing and analysis directly on the sensors in a decentralized way. This shift in paradigm introduces a shift in the privacy and security problems that need to be addressed. While a decentralized implementation avoids the single point of failure problem that typically applies to centralized approaches, it is subject to other threats, such as external monitoring, and new challenges, such as the complexity of providing decentralized implementations for data mining algorithms. In this paper, we present a solution for privacy-aware distributed data mining on wireless sensor networks. Our solution uses a permissioned blockchain to avoid a single point of failure in the system. Contracts are used to construct an onion-like structure encompassing the Hoeffding trees and a route. The onion-routed query conceals the network identity of the sensors from external adversaries, and obfuscates the actual computation to hide it from internally compromised nodes. We validate our solution on a use case related to an air quality-monitoring sensor network. We compare the quality of our model against traditional models to support the feasibility and viability of the solution.

The Raspadalica Cliff is an almost vertical 100 m high limestone cliff with a railway line at its foot and is known for numerous rockfall occurrences in the past. This article presents the results of the geotechnical study of the cliff based on a traditional geological and geotechnical field survey and remote sensing analysis. Both the traditional geological and geotechnical field survey and remote sensing surveys and analyses enabled the establishment of the structural model of the Raspadalica Cliff and the determination of the discontinuity sets and discontinuity features, such as orientation, spacing, persistence, roughness, discontinuity wall strength, aperture, degree of weathering of discontinuity wall, seepage conditions, and the presence and hardness of discontinuity filling. Kinematic analyses were performed on five cliff zones with slightly different structural features, indicating a relatively low probability of typical failures in the cliff rock mass that precede the rockfall occurrences. Although rockfall phenomena from the cliff face are relatively frequent, the kinematic analyses did not indicate a high probability of their occurrence. The aim of this manuscript is to make scientists and practitioners aware that investigation of rock mass cliffs and possible rockfall failures must not be based on usual methods without critical review of the obtained results and consequences. The combined use of traditional geological and geotechnical methods and more commonly used advanced remote sensing methods leads to better modelling, while the analysis of more associated failure modes can explain the triggering of rockfall.

The paper investigates the effects of roller pressing on the hardness, roughness, and elastic modulus of wooden workpieces. For research purposes, a roller pressing device based on purely mechanical processing was designed and developed. Four different levels of pressing force have been applied to eight different types of wood: cherry, fir, alder, linden, beech, walnut, oak, and ash. The obtained results indicate that the proposed processing method can significantly improve the hardness, elastic modulus, and surface quality of wooden workpieces. The ash sample exhibited the largest relative increase in hardness (175.9%), while the most significant relative increase in the elastic modulus (66.73%) was measured on the linden sample. The largest relative decrease in surface roughness (54.75%) was achieved on the alder sample. For all types of wood except for fir, in which case an increase in pressing force did not produce the desired reduction of roughness, correlation coefficients indicate a strong relationship between the pressing force as an input variable and the elastic modulus, hardness, and roughness as output variables.

We report on a new class of ZnO/ZnS nanomaterials based on the wurtzite/sphalerite architecture with improved electronic properties. Semiconducting properties of pristine ZnO and ZnS compounds and mixed ZnO1−xSx nanomaterials have been investigated using ab initio methods. In particular, we present the results of our theoretical investigation on the electronic structure of the ZnO1−xSx (x = 0.20, 0.25, 0.33, 0.50, 0.60, 0.66, and 0.75) nanocrystalline polytypes (2H, 3C, 4H, 5H, 6H, 8H, 9R, 12R, and 15R) calculated using hybrid PBE0 and HSE06 functionals. The main observations are the possibility of alternative polytypic nanomaterials, the effects of structural features of such polytypic nanostructures on semiconducting properties of ZnO/ZnS nanomaterials, the ability to tune the band gap as a function of sulfur content, as well as the influence of the location of sulfur layers in the structure that can dramatically affect electronic properties. Our study opens new fields of ZnO/ZnS band gap engineering on a multi-scale level with possible applications in photovoltaics, light-emitting diodes, laser diodes, heterojunction solar cells, infrared detectors, thermoelectrics, or/and nanostructured ceramics.

Most CycleGAN domain transfer architectures require a large amount of data belonging to domains on which the domain transfer task is to be applied. Nevertheless, in many real-world applications one of the domains is reduced, i.e., scarce. This means that it has much less training data available in comparison to the other domain, which is fully observable. In order to tackle the problem of using CycleGAN framework in such unfavorable application scenarios, we propose and invoke a novel Bootstrapped SSL CycleGAN architecture (BTS-SSL), where the mentioned problem is overcome using two strategies. Firstly, by using a relatively small percentage of available labelled training data from the reduced or scarce domain and a Semi-Supervised Learning (SSL) approach, we prevent overfitting of the discriminator belonging to the reduced domain, which would otherwise occur during initial training iterations due to the small amount of available training data in the scarce domain. Secondly, after initial learning guided by the described SSL strategy, additional bootstrapping (BTS) of the reduced data domain is performed by inserting artifically generated training examples into the training poll of the data discriminator belonging to the scarce domain. Bootstrapped samples are generated by the already trained neural network that performs transferring from the fully observable to the scarce domain. The described procedure is periodically repeated during the training process several times and results in significantly improved performance of the final model in comparison to the original unsupervised CycleGAN approach. The same also holds in comparison to the solutions that are exclusively based either on the described SSL, or on the bootstrapping strategy, i.e., when these are applied separately. Moreover, in the considered scarce scenarios it also shows competitive results in comparison to the fully supervised solution based on the pix2pix method. In that sense, it is directly applicable to many domain transfer tasks that are relying on the CycleGAN architecture.

Indoor Air Quality monitoring is a major asset to improving quality of life and building management. Today, the evolution of embedded technologies allows the implementation of such monitoring on the edge of the network. However, several concerns need to be addressed related to data security and privacy, routing and sink placement optimization, protection from external monitoring, and distributed data mining. In this paper, we describe an integrated framework that features distributed storage, blockchain-based Role-based Access Control, onion routing, routing and sink placement optimization, and distributed data mining to answer these concerns. We describe the organization of our contribution and show its relevance with simulations and experiments over a set of use cases.

The fields of micro- and nanomechanics are strongly interconnected with the development of micro-electro-mechanical (MEMS) and nano-electro-mechanical (NEMS) devices, their fabrication and applications. This article highlights the biomimetic concept of designing new nanodevices for advanced materials and sensing applications.

During transients that occur in an electric network, large currents can flow and large electromagnetic torques can be developed in electric generators. Accurate calculation of currents and magnetic fields during transients is an important element in the optimal design of generators and network parts, as well as mechanical parts of machines and other torque transmission parts. This paper describes the modeling of a sudden three-phase short-circuit on a synchronous generator using the finite element method (FEM) and the dynamic model. The model for simulations that use the FEM was built in the MagNet software package, and the dynamic model is embedded in the MATLAB/Simulink software package. The dynamic simulation model of a part of a network with two identical generators, represented by equivalent parameters, was developed. The results obtained after the simulation of a sudden three-phase fault in the generators by both methods are presented, including three-phase voltages, three-phase currents, machine speeds, excitation voltages, and mechanical power. In particular, the short-circuit current in the phase with the highest peak value was analyzed to determine the accuracy of the equivalent parameters used in the dynamic model. Finally, the results of these two calculation methods are compared, and recommendations are presented for the application of different modeling methods.

The automatic generation of building boundaries in contemporary research and engineering projects and practices is dominantly characterized by interior functional constraints. As a basis for the automated generation of various building boundaries, the solution presented in this paper is a novel approach that ignores the internal (functional) and focuses only on the external (non-functional) impacts. The primary orientation on external impacts may be, at any instance, extended by suitable complementary traditional methodology. The applied research methodology and presented method rely on a developed extendible rule-based system that simplifies floor plan creation by the recursive application of a formulated spatial grid generation algorithm. Based on starting parameter values (mainly the lot and building area spaces) the algorithm tends to create a set of grids that satisfy initial constraints by marking the individual grid cells as a part of the building or empty. The presented conceptual framework model served as a foundation for creating a prototype software application that supports the experimental generation of grid arrays that are transformed into readable images of residential building boundaries. For the initial validation of the developed methodology, method, and algorithm, the concrete parametric resolution is set to 1 m. The comparative analysis has shown that the presented approach overcomes some of the limitations of previous related research that generate building boundaries in simple rectangular form or with limited variability. The proposed method, in its current stage, outperforms discussed existing methods concerning complex shape boundary building plan generation. Besides that, there is a broad space for further enhancement directions concerning the interoperability with other, independently developed, frameworks, and software tools.

A contemporary approach to the spatial design of healthcare care facilities faces numerous challenges at the crossroads of multidisciplinary topics of architecture and urbanism, healthcare, security, and organisational sciences. Due to the unique combination of uses, users and architectural expression, they are defined as urban nodes. With their inclusion, architects facilitate a better placing of healthcare facilities, indirectly improving human health. The purpose of the article is to seek guidelines for the siting of healthcare facilities to provide suitable and equal healthcare to different social structures, and for the optimal and fair spatial distribution of healthcare services. The descriptive method was used to review literature on the siting of healthcare facilities based on the purpose of their operation, demographic changes, environmental characteristics, and the impact on public health. This method was selected as it facilitates data acquisition from various sources and a comprehensive understanding of the topic discussed. The results of the research show how important the impact of the healthcare care facilities siting on human health and the wider social significance of the topic discussed is. The findings may provide guidelines and proposals for future spatial decisions.

Histopathological alterations in various fish organs have a pronounced value in aquatic toxicology and are widely used in environmental monitoring. The aim of this study was to evaluate whether histopathological alterations in fish gills can discriminate seasonal variations in environmental conditions within the same aquatic ecosystem, and if so, which alterations contributed the most to seasonal differentiation. Microscopic examination of common bream Abramis brama gills displayed various alterations in gill structure, including epithelial hypertrophy, hyperplasia, mucous and chloride cell alterations, epithelial lifting, necrosis, hyperemia and aneurism. These alterations were subsequently quantified by a semi-quantitative analysis in order to detect differences in the intensity of the mentioned alterations. Epithelial hypertrophy, hyperplasia, epithelial lifting and necrosis varied significantly between seasons with only necrosis being significantly higher in the first season. Discriminant canonical analysis displayed that epithelial hyperplasia, mucous cell alterations, epithelial lifting and necrosis contributed the most to discrimination between seasons. Overall, this study demonstrates that histopathological biomarkers in fish gills can be used in discriminating seasonal variations in water quality within the same aquatic ecosystem.

Modern footbridges are often lively structures, characterized by natural frequencies that fall in the range of pedestrian activities, such as walking, running, and jumping. Therefore, serviceability assessment under human-induced excitation is crucial both at the design stage and during the footbridge lifetime. This paper presents and validates two different FE models of an existing footbridge with very complex geometry: the Streicker Footbridge at the Princeton University Campus. It represents a benchmark in the field as a testbed for vibration serviceability assessments under pedestrian excitation. The real structure is equipped with strain and temperature sensors that are currently used to collect measurements in both static and dynamic modes for research and educational purposes in Structural Health Monitoring (SHM). Based on detailed drawings of the Streicker Footbridge, a three-dimensional beam-based model was developed to represent the complex behavior of the full-scale benchmark bridge. Subsequently, a more refined discretization of the bridge deck adopting shell elements was inserted. The bridge Finite Element models were validated against available SHM data concerning static and dynamic tests. The relevant ANSYS APDL script files along with an example of pedestrian jumping application are available upon request for further research developments on the relationship between pedestrians and the benchmark footbridge.

A general four-step transformation of alkyl, cycloalkyl, aryl, and heteroaryl methyl ketones via 3-(dimethylamino)-1-substituted-prop-2-en-1-ones, followed by microwave [2+2] cycloaddition of dimethyl acetylenedicarboxylate, cyclization of (2E,3E)-2-[(dimethylamino)methylene]-3-(2-substituted)succinates with ammonia or hydroxylamine hydrochloride into 2-substituted-pyridine-4,5-dicarboxylates and their N-oxides and final cyclization with hydrazine hydrate into of 7-substituted-2,3-dihydropyrido[3,4-d]pyridazine-1,4-diones and 1,4-dioxo-7-substituted-1,2,3,4-tetrahydropyrido[4,3-d]pyridazine 6-oxides is shown.

In this paper, we describe an investigation of brain activity while playing a serious game (SG). A SG is focused on improving logical thinking, specifically on cognitive training of students in the field of basic logic gates, and we summarize SG description, design, and development. A method based on various signal processing techniques for evaluating electroencephalographic (EEG) data was implemented in the MATLAB. This assessment was based on the analysis of the spectrogram of particular brain activity. Changes in brain activity power at a characteristic frequency band during the gameplay were calculated from the spectrogram. The EEG of 21 respondents was measured. Based on the results, the respondents can be divided into three groups according to specific EEG activity changes during the gameplay compared to a relaxed state. The beta/alpha ratio, an indicator of brain employment to a mental task, was increased during gameplay in 18 of the 21 subjects. Our results reflected the sex of respondents, time of the game and the indicator, and whether the game was successfully completed.

The paper deals with the separation of the third cervical vertebra using the software VGStudio MAX, Mimics, and inVesalius. During the separation, various parameters of the threshold were used to determine the effect. The comparison of models from Mimics and inVesalius to VGStudio MAX showed that the cumulative variance distribution for 95% surface coverage is less than 0.935 mm. When comparing medically oriented software, Mimics and inVesalius, the deviation was less than 0.356 mm. The model was made of polylactic acid (PLA) material on a low-cost 3D printer, Prusa i3 MK2.5 MMU1. The printed model was scanned by four scanners: Artec Eva, 3Shape D700, Steinbichler Comet L3D, and Creaform EXAscan. The outputs from the scanners were compared to the reference model (standard tessellation language (STL) model for 3D printing) as well as to the scanner with the best accuracy (3Shape). Compared to the publications below, the analysis of deviations was evaluated on the entire surface of the model and not on selected dimensions. The cumulative variance distribution for comparing the output from the 3D scanner with the reference model, as well as comparing the scanners, shows that the deviation for 95% of the surface coverage is at the level of 0.300 mm. Since the model of the vertebra is planned for education and training, the used software and technologies are suitable for use in the design and the production process.

This work presents a study on thermo-optical properties of three Schiff bases (imines) in the solid state. The Schiff bases were obtained by means of mechanochemical synthesis using monosubstituted o-hydroxy aromatic aldehydes and monosubstituted aromatic amines. The keto-enol tautomerism and proton transfer via intramolecular O∙∙∙N hydrogen bond of the reported compounds was found to be influenced more by supramolecular interactions than by a temperature change. All products were characterised by powder X-ray diffraction (PXRD), FT-IR spectroscopy, thermogravimetric (TG) analysis and differential scanning calorimetry (DSC). Molecular and crystal structures of compounds 1, 2 and 3 were determined by single crystal X-ray diffraction (SCXRD). The molecules of 1 appear to be present as the enol-imine, the molecules of 2 as the keto-amine tautomer and the molecules of 3 exhibit keto-enol tautomeric equilibrium in the solid state. An analysis of Cambridge structural database (CSD) data on similar imines has been used for structural comparison. This work is licensed under a Creative Commons Attribution 4.0 International License.

Nanotubes made of boron nitride (BN) and carbon have attracted considerable attention within the literature due to their unique mechanical, electrical and thermal properties. In this work, BN and carbon nanotubes, exhibiting high purity (>99%) and similar surface areas (~200 m2/g), were systematically investigated for their thermal stability and oxidation behavior by combining thermal gravimetric analysis and differential scanning calorimetry methods at temperatures of up to ~1300 °C under a synthetic air flow environment. The BN nanotubes showed a good resistance to oxidation up to ~900 °C and fully transformed to boron oxide up to ~1100 °C, while the carbon nanotubes were stable up to ~450 °C and almost completely combusted up to ~800 °C. The different oxidation mechanisms are attributed to the different chemical nature of the two types of nanotubes.

Building accurate and compact classifiers in real-world applications is one of the crucial tasks in data mining nowadays. In this paper, we propose a new method that can reduce the number of class association rules produced by classical class association rule classifiers, while maintaining an accurate classification model that is comparable to the ones generated by state-of-the-art classification algorithms. More precisely, we propose a new associative classifier that selects “strong” class association rules based on overall coverage of the learning set. The advantage of the proposed classifier is that it generates significantly smaller rules on bigger datasets compared to traditional classifiers while maintaining the classification accuracy. We also discuss how the overall coverage of such classifiers affects their classification accuracy. Performed experiments measuring classification accuracy, number of classification rules and other relevance measures such as precision, recall and f-measure on 12 real-life datasets from the UCI ML repository (Dua, D.; Graff, C. UCI Machine Learning Repository. Irvine, CA: University of California, 2019) show that our method was comparable to 8 other well-known rule-based classification algorithms. It achieved the second-highest average accuracy (84.9%) and the best result in terms of average number of rules among all classification methods. Although not achieving the best results in terms of classification accuracy, our method proved to be producing compact and understandable classifiers by exhaustively searching the entire example space.

The influence of material characteristics—i.e., type or surface texture—to wetting properties is nowadays increased by the implementation of ultrafast lasers for nanostructuring. In this account, we exposed multilayer thin metal film samples of different materials to a femtosecond laser beam at a 1030 nm wavelength. The interaction generated high-quality laser-induced periodic surface structures (LIPSS) of spatial periods between 740 and 790 nm and with maximal average corrugation height below 100 nm. The contact angle (CA) values of the water droplets on the surface were estimated and the values between unmodified and modified samples were compared. Even though the laser interaction changed both the surface morphology and the chemical composition, the wetting properties were predominantly influenced by the small change in morphology causing the increase in the contact angle of ~80%, which could not be explained classically. The influence of both surface corrugation and chemical composition to the wetting properties has been thoroughly investigated, discussed and explained. The presented results clearly confirm that femtosecond patterning can be used to mold wetting properties.

The lattice fracture model is a discrete model that can simulate the fracture process of cementitious materials. In this work, the Delft lattice fracture model is reviewed and utilized for fracture analysis. First, a systematic calibration procedure that relies on the combination of two uniaxial tensile tests is proposed to determine the input parameters of lattice elements—tensile strength, compressive strength and elastic modulus. The procedure is then validated by simulating concrete fracture under complex loading and boundary conditions: Uniaxial compression, three-point bending, tensile splitting, and double-edge-notch beam shear. Simulation results are compared to experimental findings in all cases. The focus of this publication is therefore not only on summarizing existing knowledge and showing the capabilities of the lattice fracture model; but also to fill in an important gap in the field of lattice modeling of concrete fracture; namely, to provide a recommendation for a systematic model calibration using experimental data. Through this research, numerical analyses are performed to fully understand the failure mechanisms of cementitious materials under various loading and boundary conditions. While the model presented herein does not aim to completely reproduce the load-displacement curves, and due to its simplicity results in relatively brittle post-peak behavior, possible solutions for this issue are also discussed in this work.

This paper presents one of the ways in which the ideas of active learning, problem solving, using history of science, probing students' ideas and other approaches can be implemented to bring about meaningful learning. The example is taken from the plant chemistry and is suitable for the lower secondary level. In this paper we wanted to show how, from a seemingly simple question "What's inside a sweet pepper fruit", one can develop a complex teaching situation that leads to the realisation of teaching goals in a unique way. It shows merely one approach as an example of how to connect content (i.e. declarative knowledge, practical skills) and understanding of scientific processes (i.e. process-based knowledge), as well as the understanding of their own thought processes (i.e. metacognitive knowledge). The chemical analysis of the gases in the sweet pepper fruit showed that there was an increased concentration of carbon dioxide which is around 200 times greater than in the air and this is perhaps a good starting point for new problem-based teaching. (Contains 8 figures.)

Alignment-free, three dimensional structure–activity relationships (3D QSAR) of the antiproliferative potency of twenty-two glutarimide-containing compounds, taken from National Cancer Institute Developmental therapeutics Program database, toward eight representative human tumour cell lines are reported. The descriptors used in the QSAR study were derived from GRID molecular interaction fields. The obtained models readily detect structural motifs positively or negatively correlated with the potency of the studied compounds toward each cell line. In this way, the pharmacophoric pattern required for high potency of compounds is reported. This pattern can serve as guidance for the design and syntheses of novel congeners, planned to be tested toward human tumour cell lines.

Human origin recognition complex 4 (ORC4) protein, a subunit of the origin recognition complex, belongs to the AAA+ superfamily of adenosine triphosphate (ATP) ases. Proteins belonging to this family require ATP for their function and interactions with ATP lead to conformational changes in them or in their partners. Human ORC4 protein induces structural changes in DNA substrates, promoting renaturation and formation of non-canonical structures, as well as conversion of single-stranded into multi-stranded oligonucleotide structures. The aim of this study was to further investigate the role of ATP in the function of human ORC4 protein. For this purpose, a mutant in the conserved Walker B motif of ORC4, which is able to bind but not to hydrolyze ATP, was constructed and its activity in DNA restructuring reactions was investigated. The obtained results showed that ATP hydrolysis is not necessary for the function of human ORC4. It is proposed that ATP has a structural role as a cofactor in the function of human ORC4 as a DNA restructuring agent.

Coniferous wood (fir) was transformed by pyrolysis into carbon preforms, which were subsequently converted into biomorphic ceramics by the pressure infiltration technique with colloidal silica. An in situ reaction between the silica and the carbon template occurred in the cellular wall at a high sintering temperature. Depending on the employed atmosphere, non-oxide (SiC) or oxide (SiO2) ceramics were obtained. The morphology of the resulting porous ceramics and their phase composition were investigated by scanning electron microscopy (SEM/EDX) and X-ray diffraction (XRD). The experimental results showed that the biomorphic cellular morphology of the wood maintained in both the SiC and silica ceramics, which consisted of only the b-SiC phase and SiO2, respectively.

The protolytic equilibria of 13 4-aryl-2,4-dioxobutanoic acids (ADKs) were spectrophotometrically studied in aqueous solutions in the pH range 1–9 at 25±1 °C and an ionic strength of 0.1 mol l-1 (NaCl), with the exception of the 4-OH- derivative which was also potentiometrically studied in the pH range 7–10 at 25±1 °C and an ionic strength of 0.1 mol l-1 (NaCl). In solution, the compounds simultaneously exist in one diketo and two enolic forms; therefore, the determined acidity constants (pKa1 1.87–2.29, pKa2 6.63–8.13 and pKa3(4-OH-) 9.52) represent system macro constants. The 1H-NMR spectrum of the basic compound (4-phenyl-2,4-dioxobutanoic acid) (25 °C, pD 5.0) proved the existence of all tautomeric forms. Using the extended Hammett relation, the determined pKa values were correlated with literature σ values. The predicted pKa values were in fair accordance with the experimentally observed ones. Molecular, monoanionic and dianionic forms of the basic compound were optimized by the semi-empirical molecular orbital PM6 method using the implicit water solvation model (COSMO). The obtained geometries were used to explain the quality of the LFER models.

The possibility of using diatomaceous earth as Si precursor for low temperature synthesis of non-oxide powders by carbothermal reduction-nitridation was studied. It was found that carbonitriding reactions produce phases of the Si–Al–O–N system. Already at 1300 °C, nanosized, non-oxide powders were obtained. The comparatively low reaction temperatures is attributred to the nano-porous nature of the raw material. The evolution of crystalline phases proceeded via many intermediate stages. The powders were characterized by X-ray and SEM investigations. The results showed that diatomaceous earth can be a very effective source for obtaining non-oxide powders.

It is shown how a simple theoretical approach can be used for the investigation of electro-organic reactions.Mononitroimidazoles and mononitropyrazoles were studied by the semiempirical MNDO-PM3 molecular orbital method. The electrochemical reduction potentials of diazoles have been correlated with the energy of the lowest unoccupied molecular orbital (LUMO). It was found that an admirable correlation could be obtained by the introduction of simple structural descriptors as a correction to the energy of the LUMO. The interaction of a molecule with its surrounding depends on electrostatic potential and on steric hindrance. Most of these steric effects are taken into account using two parameters having a very limited set of integer values. The first (b) is the position of a ring substituent regarding ring nitrogens, which accounts for the different orientations of dipole moments and for the different shape of the electrostatic potential. The second (structural) parameter (t) is the type of the ring, which accounts mostly for different modes of electrode approach, and for different charge polarization patterns in two diazole rings. The extended correlation with ELUMO, b and t, is very good, having a regression coefficient r = 0.991. The intrinsic importance of b and t is exemplified by their high statistical weight.

The effects of temperature on the thermal conductivity of Si3N4 sintered with Li-exchanged zeolite were investigated. The highest conductivity was measured for the ceramics sintered with 10 % of additive. The complete a->b-Si3N4 transformation and maximum density (> 98 % TD) were attained with the sample sintered at 1650 ºC. However, the results show that Al and O from the additive dissolve into the b-Si3N4 structure which act as phonon scattering sites resulting in a lowering of the conductivity and a weaker temperature dependance of the conductivity.

A series of acrylate functionalized samples based on hyperbranched hydroxy-terminated polyesters with different molecular weights and different degrees of acrylation were synthesized. The obtained urethane acrylates were slightly yellow viscose liquids. Their composition was characterized by FTIR and 1H-NMR spectroscopy and their molecular weights were measured by GPC. All the synthesized samples were diluted with 25 wt.% 1,4-butanediol dimethacrylate (BDDM). The rheological properties of the uncured samples and the dynamic mechanical properties of the UV cured samples were examined. All the samples exhibit Newtonian behavior, which indicates the absence of physical entanglements in these polymers. The viscosity increases with increasing number of acrylic groups per molecule. The glass transition temperature of the UV cured samples increases with increasing the number of acrylic groups per molecule. The value of the storage modulus in the rubber-elastic plateau and the cross-link density increase with increasing number of acrylic groups per molecule. The formed networks are inhomogeneous and the residual unsaturation is the highest in the samples with the largest number of acrylic groups per molecule.

Local and conventional raw materialsmassive basalt from the Vrelo locality on Kopaonik mountainhave been used as starting materials to test their suitability for the production of glass-ceramics. Crystallization phenomena of glasses of the fused basalt rocks were studied by X-ray phase analysis, optical microscopy and other techniques. Various heat treatments were used, and their influences, on controlling the microstructures and properties of the products were studied with the aim of developing high strength glass-ceramic materials. Diopside CaMg(SiO3)2 and hypersthene ((Mg,Fe)SiO3) were identifies as the crystalline phases. The final products contained considerable amounts of a glassy phase. The crystalline size was in range of 8480 mm with plate or needle shape. Microhardness, crashing strength and wears resistence of the glass-ceramics ranged from 6.57.5, from 20006300 kg/cm2 and from 0.10.2 g/cm, respectively.